Abstract
In this paper the analysis of microscopic liver tissue images is addressed to identify abnormal zones due to the presence of tissue with necrosis, or to malignant lymphoma; the study is performed by texture analysis. A discrete level set approach is considered, applying the well know segmentation algorithm to a new data constituted by a linear combination of the matrices of Uniformity, Contrast and Entropy. The proposed method makes use of the classification capability of the discrete level set analysis applied to a suitable transformation of the original data. The algorithm is applied to a significant set of liver tissue, showing encouraging results.
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Ahmadian, A., Mostafa, A., Abolhassani, M.D., Salimpou, Y.: A texture classification method for diffused liver diseases using Gabor wavelets. In: Proceedings of the IEEE Engineering in Medicine and Biology 27th Annual Conference, pp.1567–1570, Shanghai, China(2005)
Balasubramanian, D., Srinivasan, P., Gurrupatham, R.: Automatic classification of focal lesions in ultrasound liver images using principal component analysis and neural networks. In: Proceedings of the 29th Annual International Conference of the IEEE EMBS, pp.2134–2137, Lyon(2007)
Besson, S.J., Barlaud, M., Aubert, G.: Image segmentation using active contours: calculus of variations for shape gradients? SIAM J. Appl. Math. 63, 2128–2154(2003)
De Santis, A., Iacoviello, D.: A discrete level set approach for image segmentation. Signal Image Video Process. 1, 303–320(2007)
De Santis, A., Iacoviello, D.: Robust real time eye tracking for computer interface for disabled people. Comput. Methods Programs Biomed. 96, 1–11(2009)
Gonzales, R.C., Woods, R.E.: Digital Image Processing. Prentice hall Inc, NJ. SMC-3 6, 610–621 (2002)
Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. SMC-3 6, 610–621(1973)
Horng, M.H.: An ultrasonic image evaluation system for assessing the severity of chronic liver disease. Comput. Med. Imag. Graph. 31, 485–491(2007)
Imen, K., Fablet, R., Boucher, J.M., Augustin, J.M.: Region- based and incidence angle dependent segmentation of seabed sonar images using a level set approach combined to local texture statistics. Asia Pacific Oceans 2006, 1–7(2007)
Lu, Z., Song, E., Wang, Q., Wang, X.: The liver fibrosis identification based on color 2D wavelet transform for the medical image. In: Proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, pp.205–208, Hong Kong(2008)
Masutani, Y., Uozumi, K., Akahane, M., Ohtomo, K.: Liver CT image processing: a short introduction of the technical elements. Eur. J. Tadiol. 58, 246–251(2006)
Pham, M., Susomboon, R., Disney, T., Raicu, D., Furst, J.: A comparison of texture models for automatic liver segmentation. In: Proceedings of SPIE Medical Imaging(2007)
Zhang, X., Fujita, H., Kanematsu, M., Zhou, X., Hara, T., Kato, H., Yokoyama, R., Hoshi, H.: Improving the classification of cirrhotic liver by using texture features. In: Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, pp.867–870, Shanghai, China(2005)
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Iacoviello, D. (2011). A Discrete Level Set Approach for Texture Analysis of Microscopic Liver Images. In: Tavares, J., Jorge, R. (eds) Computational Vision and Medical Image Processing. Computational Methods in Applied Sciences, vol 19. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0011-6_6
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DOI: https://doi.org/10.1007/978-94-007-0011-6_6
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